This book covers several cutting-edge topics and provides a direct follow-up to former publications such as “Intent-based Networking” and “Emerging Networking”, bringing together the latest network technologies and advanced AI applications. Typical subjects include 5G/6G, clouds, fog, leading-edge LLMs, large-scale distributed environments with specific QoS requirements for IoT, robots, machine and deep learning, chatbots, and further AI solutions. The highly promising combination of smart applications, network infrastructure, and AI represents a unique mix of real synergy. Special aspects of current importance such as energy efficiency, reliability, sustainability, security and privacy, telemedicine, e-learning, and image recognition are addressed too. The book is suitable for students, professors, and advanced lecturers for networking, system architecture, and applied AI. Moreover, it serves as a basis for research and inspiration for interested professionals looking for new challenges.

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business.

This book presents the role of AI-Driven Digital Twin in the Industry 4.0 ecosystem by focusing on Smart Manufacturing, sustainable development, and many other applications. It also discusses different case studies and presents an in-depth understanding of the benefits and limitations of using AI and Digital Twin for industrial developments. AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. The book also enables familiarity with various industrial applications of computational and communication technologies and summarizes the ongoing research and innovations in the areas of AI, Digital Twin, and Smart Manufacturing while also tracking the various research challenges along with future advances. This reference book is a must-read and is very beneficial to students, researchers, academicians, industry experts, and professionals working in related fields.

This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.

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